Emc IP Holding Company LLC

Ana Paskal

Martin Rosa

Guy Eisenkot

Yuval Shachak

Maria Oks

Shay Menaia

Yaron De Levie

Miri Weissler

Lior Govrin

Barak Schoster

Methods, apparatus, and processor-readable storage media for evaluating cyber attacker behavior using machine learning to identify anomalies are provided herein. An example method includes obtaining, based on events associated with changes in one or more of a registry and a computer process, baseline models comprising a user context representing normal behavior for a first subset of features associated with the events with respect to a given user, an inverse context that represents normal behavior for at least one feature with respect to a particular value of one or more features in the first subset, and a global context representing a behavior of the features across the plurality of users; detecting a new event attributable to the given user; calculating a score for the new event using one or more of the baseline models; and determining that the new event is an anomaly in response to the score satisfying a threshold.

Anomaly detection based on evaluation of user behavior using multi-context machine learning

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Rishon LeTsiyon, Israel

Ana Paskal